{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "\n",
    "X_train_path = \"public/X_train.csv\"\n",
    "X_test_path = \"public/X_test.csv\"\n",
    "y_train_path = \"public/y_train.csv\"\n",
    "\n",
    "X = pd.read_csv(X_train_path, index_col=\"id\")\n",
    "X_out = pd.read_csv(X_test_path, index_col=\"id\")\n",
    "y = pd.read_csv(y_train_path, index_col=\"id\")\n",
    "\n",
    "X.shape, y.shape, X_out.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "((5117, 17807), (3411, 17807))"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.preprocessing import MinMaxScaler\n",
    "\n",
    "scaler = MinMaxScaler(feature_range=(-100, 100))\n",
    "\n",
    "# Scale each row individually for X_train\n",
    "X = X.apply(lambda row: pd.Series(scaler.fit_transform(row.values.reshape(-1, 1)).ravel()), axis=1)\n",
    "\n",
    "# Scale each row individually for X_test\n",
    "X_out = X_out.apply(lambda row: pd.Series(scaler.fit_transform(row.values.reshape(-1, 1)).ravel()), axis=1)\n",
    "\n",
    "X.shape, X_out.shape\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x1000 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import biosppy.signals.ecg as ecg\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# Extract the R peaks from the first row of X_train\n",
    "\n",
    "fig, axs = plt.subplots(4, 1, figsize=(5, 10))\n",
    "for i in range(100):\n",
    "    row = X.loc[i].dropna().to_numpy(dtype='float32')\n",
    "    rpeaks, = ecg.engzee_segmenter(signal=row, sampling_rate=300)\n",
    "    beat = ecg.extract_heartbeats(signal=row, rpeaks=rpeaks, sampling_rate=300)\n",
    "    peak_distances = pd.Series(beat['rpeaks']).diff().dropna()\n",
    "\n",
    "    axs[y.loc[i, 'y']].plot(peak_distances, color='black')\n",
    "    # Iterate over the classes and plot the peak distances\n",
    "\n",
    "# Adjust the layout\n",
    "plt.tight_layout()\n",
    "\n",
    "# Show the plots\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "import biosppy.signals.ecg as ecg\n",
    "import numpy as np\n",
    "from scipy.stats import skew, kurtosis\n",
    "from scipy.fftpack import fft\n",
    "from scipy.signal import welch\n",
    "from scipy.stats import entropy\n",
    "import pywt\n",
    "\n",
    "\n",
    "# Define a function to extract time domain features\n",
    "def extract_ecg_features(data, i):\n",
    "    # Compute the heart rate\n",
    "    row = data.loc[i].dropna().to_numpy(dtype='float32')\n",
    "    ts, filtered, rpeaks, templates_ts, templates, heart_rate_ts, heart_rate = ecg.ecg(signal=row, sampling_rate=300, show=False)\n",
    "\n",
    "    # Return the extracted features\n",
    "    return ts, filtered, rpeaks, templates_ts, templates, heart_rate_ts, heart_rate\n",
    "\n",
    "\n",
    "def extract_time_features(data):\n",
    "    # Compute the mean RR interval\n",
    "    mean_rr = np.mean(np.diff(data))\n",
    "\n",
    "    # Compute the standard deviation of RR intervals\n",
    "    std_rr = np.std(np.diff(data))\n",
    "\n",
    "    # Compute the root mean square of successive RR interval differences\n",
    "    rms_rr = np.sqrt(np.mean(np.square(np.diff(data))))\n",
    "\n",
    "    # Compute the skewness of RR intervals\n",
    "    skew_rr = skew(np.diff(data))\n",
    "\n",
    "    # Compute the kurtosis of RR intervals\n",
    "    kurt_rr = kurtosis(np.diff(data))\n",
    "\n",
    "    # Return the extracted features\n",
    "    return mean_rr, std_rr, rms_rr, skew_rr, kurt_rr\n",
    "\n",
    "def extract_frequency_features(data, fs=300):\n",
    "    # Compute the FFT of the signal\n",
    "    if(data.shape[0] == 0):\n",
    "        return None, None\n",
    "    fft_values = fft(data)\n",
    "    fft_values = 2.0*np.abs(fft_values[:fs//2])/len(data)\n",
    "\n",
    "    # Compute the power spectral density of the signal\n",
    "    freqs, psd_values = welch(data, fs=fs)\n",
    "\n",
    "    # Compute the peak frequency\n",
    "    # peak_freq = freqs[np.argmax(psd_values)]\n",
    "\n",
    "    # Compute the median frequency\n",
    "    median_freq = freqs[len(freqs)//2]\n",
    "\n",
    "    # Compute the spectral entropy\n",
    "    spectral_entropy = entropy(psd_values)\n",
    "\n",
    "    # Return the extracted features\n",
    "    return median_freq, spectral_entropy\n",
    "\n",
    "import numpy as np\n",
    "\n",
    "def calculate_poincare_descriptors(rr_intervals):\n",
    "    # Calculate the differences between successive RR intervals\n",
    "    rr_diff = np.diff(rr_intervals)\n",
    "\n",
    "    # Calculate SD1 and SD2\n",
    "    sd1 = np.sqrt(np.std(rr_diff, ddof=1) ** 2 * 0.5)\n",
    "    sd2 = np.sqrt(2 * np.std(rr_intervals, ddof=1) ** 2 - 0.5 * np.std(rr_diff, ddof=1) ** 2)\n",
    "\n",
    "    return sd1, sd2\n",
    "\n",
    "\n",
    "def extract_wavelet_features(signal, wavelet='db4', level=3):\n",
    "    if(signal.shape[0] == 0):\n",
    "        return [None, None, None, None], [None, None, None, None]\n",
    "\n",
    "    # Compute the wavelet coefficients\n",
    "    coeffs = pywt.wavedec(signal, wavelet, level=level)\n",
    "\n",
    "    # Compute the standard deviation of each set of coefficients\n",
    "    stds = [np.std(coeff) for coeff in coeffs]\n",
    "\n",
    "    # Compute the mean of each set of coefficients\n",
    "    means = [np.mean(coeff) for coeff in coeffs]\n",
    "\n",
    "    # Return the extracted features\n",
    "    return stds, means\n",
    "\n",
    "def extract_morphological_features(data):\n",
    "    if (data.shape[0] == 0):\n",
    "        return [None for _ in range(12)]\n",
    "\n",
    "    # Compute the R-peak amplitude\n",
    "    r_amplitude = np.max(data)\n",
    "\n",
    "    # Compute the Q and S wave amplitudes\n",
    "    max_ind = np.argmax(data)\n",
    "    q_amplitude = np.min(data[:np.argmax(data)], initial=0)\n",
    "    s_amplitude = np.min(data[np.argmax(data):], initial=0)\n",
    "\n",
    "    # Compute the T wave amplitude\n",
    "    t_amplitude = None\n",
    "    if np.argmax(data) < data.shape[0]:\n",
    "        t_amplitude = np.max(data[np.argmax(data):], initial=0)\n",
    "\n",
    "    # Compute the P wave amplitude\n",
    "    p_amplitude = None\n",
    "    if np.argmin(data) > 0:\n",
    "        p_amplitude = np.max(data[:np.argmin(data)], initial=0)\n",
    "\n",
    "    # Compute the QRS complex duration\n",
    "    qrs_duration = None\n",
    "    if np.argmax(data) > 0:\n",
    "        qrs_duration = np.argmax(data) - np.argmin(data[:np.argmax(data)])\n",
    "\n",
    "    # Compute the QT interval\n",
    "    qt_interval = None\n",
    "    if np.argmax(data) < data.shape[0] and np.argmax(data) > 0:\n",
    "        qt_interval = np.argmax(data[np.argmax(data):]) - np.argmin(data[:np.argmax(data)])\n",
    "\n",
    "    # Compute the PR interval\n",
    "    pr_interval = None\n",
    "    if(np.argmin(data) > 0):\n",
    "        pr_interval = np.argmax(data) - np.argmax(data[:np.argmin(data)])\n",
    "\n",
    "    # Compute the ST segment\n",
    "    st_segment = None\n",
    "    if np.argmax(data) < data.shape[0] and np.argmax(data) > 0:\n",
    "        st_segment = np.argmax(data[np.argmax(data):]) - np.argmax(data)\n",
    "\n",
    "    # Compute the RR interval\n",
    "    rr_interval = None\n",
    "    if len(np.where(data == np.max(data))[0]) > 1:\n",
    "        rr_interval = np.where(data == np.max(data))[0][1] - np.where(data == np.max(data))[0][0]\n",
    "\n",
    "    # Compute the P wave duration\n",
    "    p_duration = None\n",
    "    if np.argmin(data) > 0:\n",
    "        p_duration = np.argmax(data) - np.argmax(data[:np.argmin(data)])\n",
    "\n",
    "    # Compute the T wave duration\n",
    "    t_duration = None\n",
    "    if np.argmax(data) < data.shape[0] and np.argmax(data) > 0:\n",
    "        t_duration = np.argmax(data[np.argmax(data):]) - np.argmax(data)\n",
    "\n",
    "    # Return the extracted features\n",
    "    return r_amplitude, q_amplitude, s_amplitude, t_amplitude, p_amplitude, qrs_duration, qt_interval, pr_interval, st_segment, rr_interval, p_duration, t_duration\n",
    "\n",
    "\n",
    "# Extract time domain features from the first row of X_train\n",
    "ecg_features = ['ts', 'filtered', 'rpeaks', 'templates_ts', 'mean_templates', 'heart_rate_ts', 'heart_rate']\n",
    "time_features = ['mean', 'std', 'rms', 'skew', 'kurt']\n",
    "frequency_features = ['median_freq', 'spectral_entropy']\n",
    "poincarre_features = ['sd1', 'sd2']\n",
    "wavelet_features = ['wave_std', 'wave_mean']\n",
    "\n",
    "def extract_features(X_data, N):\n",
    "\n",
    "    features = pd.DataFrame(columns=ecg_features)\n",
    "\n",
    "    for i in range(N):\n",
    "        ts, filtered, rpeaks, templates_ts, templates, heart_rate_ts, heart_rate = extract_ecg_features(X_data, i)\n",
    "        mean_templates = np.mean(templates, axis=0)\n",
    "        features.loc[len(features)] = [ts, filtered, rpeaks, templates_ts, mean_templates, heart_rate_ts, heart_rate]\n",
    "\n",
    "    for ec in ecg_features:\n",
    "        tf = features[ec].map(extract_time_features)\n",
    "        for i, t in enumerate(time_features):\n",
    "            features[ec + \"_\" + t] = tf.map(lambda x: x[i])\n",
    "        ff = features[ec].map(extract_frequency_features)\n",
    "        for i, f in enumerate(frequency_features):\n",
    "            features[ec + \"_\" + f] = ff.map(lambda x: x[i])\n",
    "        pf = features[ec].map(calculate_poincare_descriptors)\n",
    "        for i, p in enumerate(poincarre_features):\n",
    "            features[ec + \"_\" + p] = tf.map(lambda x: x[i])\n",
    "        wf = features[ec].map(extract_wavelet_features)\n",
    "        for i, w in enumerate(wavelet_features):\n",
    "            wave = wf.map(lambda x: x[i])\n",
    "            for j in range(4):\n",
    "                features[ec + \"_\" + w + \"_\" + str(j)] = wave.map(lambda x: x[j])\n",
    "\n",
    "    morphological_features = ['r_amplitude', 'q_amplitude', 's_amplitude', 't_amplitude', 'p_amplitude', 'qrs_duration', 'qt_interval', 'pr_interval']\n",
    "    # print(features['templates'])\n",
    "    mf = features['mean_templates'].map(extract_morphological_features)\n",
    "    for i, m in enumerate(morphological_features):\n",
    "        features['templates_' + m] = mf.map(lambda x: x[i])\n",
    "\n",
    "    return features.drop(ecg_features, axis=1)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 66, using nperseg = 66\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 35, using nperseg = 35\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 30, using nperseg = 30\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 69, using nperseg = 69\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 46, using nperseg = 46\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 25, using nperseg = 25\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 40, using nperseg = 40\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 43, using nperseg = 43\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 64, using nperseg = 64\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 10, using nperseg = 10\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 26, using nperseg = 26\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 32, using nperseg = 32\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 37, using nperseg = 37\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 18, using nperseg = 18\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 45, using nperseg = 45\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 27, using nperseg = 27\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 13, using nperseg = 13\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 34, using nperseg = 34\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 52, using nperseg = 52\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 29, using nperseg = 29\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 17, using nperseg = 17\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 33, using nperseg = 33\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 85, using nperseg = 85\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 41, using nperseg = 41\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 83, using nperseg = 83\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 53, using nperseg = 53\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 38, using nperseg = 38\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 57, using nperseg = 57\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 42, using nperseg = 42\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 84, using nperseg = 84\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 28, using nperseg = 28\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 24, using nperseg = 24\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 19, using nperseg = 19\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 44, using nperseg = 44\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 39, using nperseg = 39\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 31, using nperseg = 31\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 55, using nperseg = 55\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 14, using nperseg = 14\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 49, using nperseg = 49\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 56, using nperseg = 56\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 47, using nperseg = 47\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 70, using nperseg = 70\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 92, using nperseg = 92\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 23, using nperseg = 23\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 11, using nperseg = 11\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 60, using nperseg = 60\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 22, using nperseg = 22\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 138, using nperseg = 138\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 61, using nperseg = 61\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 48, using nperseg = 48\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 36, using nperseg = 36\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 12, using nperseg = 12\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 81, using nperseg = 81\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 65, using nperseg = 65\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 62, using nperseg = 62\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 103, using nperseg = 103\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 112, using nperseg = 112\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 51, using nperseg = 51\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 9, using nperseg = 9\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 20, using nperseg = 20\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 58, using nperseg = 58\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 145, using nperseg = 145\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 68, using nperseg = 68\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 67, using nperseg = 67\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 21, using nperseg = 21\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 63, using nperseg = 63\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 50, using nperseg = 50\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 73, using nperseg = 73\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 71, using nperseg = 71\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 16, using nperseg = 16\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 122, using nperseg = 122\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 94, using nperseg = 94\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 87, using nperseg = 87\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 72, using nperseg = 72\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 54, using nperseg = 54\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 120, using nperseg = 120\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 75, using nperseg = 75\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 74, using nperseg = 74\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 77, using nperseg = 77\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 101, using nperseg = 101\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 109, using nperseg = 109\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 80, using nperseg = 80\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 76, using nperseg = 76\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 114, using nperseg = 114\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 15, using nperseg = 15\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 59, using nperseg = 59\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 82, using nperseg = 82\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 78, using nperseg = 78\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 116, using nperseg = 116\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 79, using nperseg = 79\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 99, using nperseg = 99\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 136, using nperseg = 136\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 117, using nperseg = 117\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 126, using nperseg = 126\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 102, using nperseg = 102\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 131, using nperseg = 131\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 7, using nperseg = 7\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 98, using nperseg = 98\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 88, using nperseg = 88\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 90, using nperseg = 90\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 100, using nperseg = 100\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 8, using nperseg = 8\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 106, using nperseg = 106\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 107, using nperseg = 107\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 111, using nperseg = 111\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 159, using nperseg = 159\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 135, using nperseg = 135\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 127, using nperseg = 127\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 86, using nperseg = 86\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 93, using nperseg = 93\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 105, using nperseg = 105\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 96, using nperseg = 96\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 6, using nperseg = 6\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 121, using nperseg = 121\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 143, using nperseg = 143\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 91, using nperseg = 91\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 129, using nperseg = 129\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 142, using nperseg = 142\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 97, using nperseg = 97\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 89, using nperseg = 89\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/pywt/_multilevel.py:43: UserWarning: Level value of 3 is too high: all coefficients will experience boundary effects.\n",
      "  warnings.warn(\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 180, using nperseg = 180\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 180, using nperseg = 180\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/numpy/core/fromnumeric.py:3504: RuntimeWarning: Mean of empty slice.\n",
      "  return _methods._mean(a, axis=axis, dtype=dtype,\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide\n",
      "  ret = ret.dtype.type(ret / rcount)\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/numpy/core/_methods.py:206: RuntimeWarning: Degrees of freedom <= 0 for slice\n",
      "  ret = _var(a, axis=axis, dtype=dtype, out=out, ddof=ddof,\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/numpy/core/_methods.py:163: RuntimeWarning: invalid value encountered in divide\n",
      "  arrmean = um.true_divide(arrmean, div, out=arrmean,\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/numpy/core/_methods.py:198: RuntimeWarning: invalid value encountered in scalar divide\n",
      "  ret = ret.dtype.type(ret / rcount)\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/stats/_stats_py.py:1193: RuntimeWarning: Mean of empty slice.\n",
      "  mean = a.mean(axis, keepdims=True)\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/numpy/core/_methods.py:121: RuntimeWarning: invalid value encountered in divide\n",
      "  ret = um.true_divide(\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/stats/_stats_py.py:1303: RuntimeWarning: Mean of empty slice.\n",
      "  mean = a.mean(axis, keepdims=True)\n",
      "/var/folders/l2/j581hbb53nb9hn1507fwv24w0000gn/T/ipykernel_1451/3273622910.py:31: RuntimeWarning: Precision loss occurred in moment calculation due to catastrophic cancellation. This occurs when the data are nearly identical. Results may be unreliable.\n",
      "  skew_rr = skew(np.diff(data))\n",
      "/var/folders/l2/j581hbb53nb9hn1507fwv24w0000gn/T/ipykernel_1451/3273622910.py:34: RuntimeWarning: Precision loss occurred in moment calculation due to catastrophic cancellation. This occurs when the data are nearly identical. Results may be unreliable.\n",
      "  kurt_rr = kurtosis(np.diff(data))\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 65, using nperseg = 65\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 34, using nperseg = 34\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 29, using nperseg = 29\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 68, using nperseg = 68\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 44, using nperseg = 44\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 22, using nperseg = 22\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 39, using nperseg = 39\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 42, using nperseg = 42\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 62, using nperseg = 62\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 9, using nperseg = 9\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 25, using nperseg = 25\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 31, using nperseg = 31\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 24, using nperseg = 24\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 36, using nperseg = 36\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 27, using nperseg = 27\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 17, using nperseg = 17\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 26, using nperseg = 26\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 12, using nperseg = 12\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 32, using nperseg = 32\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 51, using nperseg = 51\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 33, using nperseg = 33\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 16, using nperseg = 16\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 38, using nperseg = 38\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 72, using nperseg = 72\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 40, using nperseg = 40\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 28, using nperseg = 28\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 82, using nperseg = 82\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 50, using nperseg = 50\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 37, using nperseg = 37\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 52, using nperseg = 52\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 56, using nperseg = 56\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 83, using nperseg = 83\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 23, using nperseg = 23\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 43, using nperseg = 43\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 30, using nperseg = 30\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 54, using nperseg = 54\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 13, using nperseg = 13\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 41, using nperseg = 41\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 35, using nperseg = 35\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 48, using nperseg = 48\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 55, using nperseg = 55\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 46, using nperseg = 46\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 69, using nperseg = 69\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 88, using nperseg = 88\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 18, using nperseg = 18\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 63, using nperseg = 63\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 10, using nperseg = 10\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 58, using nperseg = 58\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 21, using nperseg = 21\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 137, using nperseg = 137\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 60, using nperseg = 60\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 45, using nperseg = 45\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 11, using nperseg = 11\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 80, using nperseg = 80\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 64, using nperseg = 64\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 61, using nperseg = 61\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 47, using nperseg = 47\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 20, using nperseg = 20\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 102, using nperseg = 102\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 110, using nperseg = 110\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 8, using nperseg = 8\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 19, using nperseg = 19\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 57, using nperseg = 57\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 144, using nperseg = 144\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 66, using nperseg = 66\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 91, using nperseg = 91\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 84, using nperseg = 84\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 49, using nperseg = 49\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 81, using nperseg = 81\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 70, using nperseg = 70\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 15, using nperseg = 15\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 121, using nperseg = 121\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 90, using nperseg = 90\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 86, using nperseg = 86\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 71, using nperseg = 71\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 53, using nperseg = 53\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 117, using nperseg = 117\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 67, using nperseg = 67\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 73, using nperseg = 73\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 59, using nperseg = 59\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 76, using nperseg = 76\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 74, using nperseg = 74\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 100, using nperseg = 100\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 14, using nperseg = 14\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 5, using nperseg = 5\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 108, using nperseg = 108\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 78, using nperseg = 78\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 75, using nperseg = 75\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 113, using nperseg = 113\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 6, using nperseg = 6\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 114, using nperseg = 114\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 79, using nperseg = 79\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 93, using nperseg = 93\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 98, using nperseg = 98\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 135, using nperseg = 135\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 116, using nperseg = 116\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 125, using nperseg = 125\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 7, using nperseg = 7\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 130, using nperseg = 130\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 97, using nperseg = 97\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 4, using nperseg = 4\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 99, using nperseg = 99\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 2, using nperseg = 2\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 105, using nperseg = 105\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 106, using nperseg = 106\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 77, using nperseg = 77\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 101, using nperseg = 101\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 158, using nperseg = 158\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 134, using nperseg = 134\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 126, using nperseg = 126\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 85, using nperseg = 85\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 89, using nperseg = 89\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 92, using nperseg = 92\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 104, using nperseg = 104\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 95, using nperseg = 95\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 118, using nperseg = 118\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 142, using nperseg = 142\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 1, using nperseg = 1\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/stats/_entropy.py:133: RuntimeWarning: invalid value encountered in divide\n",
      "  pk = 1.0*pk / np.sum(pk, axis=axis, keepdims=True)\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 3, using nperseg = 3\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 119, using nperseg = 119\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 96, using nperseg = 96\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/numpy/core/_methods.py:206: RuntimeWarning: Degrees of freedom <= 0 for slice\n",
      "  ret = _var(a, axis=axis, dtype=dtype, out=out, ddof=ddof,\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/numpy/core/_methods.py:163: RuntimeWarning: invalid value encountered in divide\n",
      "  arrmean = um.true_divide(arrmean, div, out=arrmean,\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/numpy/core/_methods.py:198: RuntimeWarning: invalid value encountered in scalar divide\n",
      "  ret = ret.dtype.type(ret / rcount)\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/pywt/_multilevel.py:43: UserWarning: Level value of 3 is too high: all coefficients will experience boundary effects.\n",
      "  warnings.warn(\n",
      "/var/folders/l2/j581hbb53nb9hn1507fwv24w0000gn/T/ipykernel_1451/3273622910.py:162: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n",
      "  features[ec + \"_\" + w + \"_\" + str(j)] = wave.map(lambda x: x[j])\n",
      "/var/folders/l2/j581hbb53nb9hn1507fwv24w0000gn/T/ipykernel_1451/3273622910.py:162: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n",
      "  features[ec + \"_\" + w + \"_\" + str(j)] = wave.map(lambda x: x[j])\n",
      "/var/folders/l2/j581hbb53nb9hn1507fwv24w0000gn/T/ipykernel_1451/3273622910.py:162: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n",
      "  features[ec + \"_\" + w + \"_\" + str(j)] = wave.map(lambda x: x[j])\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/numpy/core/fromnumeric.py:3504: RuntimeWarning: Mean of empty slice.\n",
      "  return _methods._mean(a, axis=axis, dtype=dtype,\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide\n",
      "  ret = ret.dtype.type(ret / rcount)\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/numpy/core/_methods.py:206: RuntimeWarning: Degrees of freedom <= 0 for slice\n",
      "  ret = _var(a, axis=axis, dtype=dtype, out=out, ddof=ddof,\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/numpy/core/_methods.py:163: RuntimeWarning: invalid value encountered in divide\n",
      "  arrmean = um.true_divide(arrmean, div, out=arrmean,\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/numpy/core/_methods.py:198: RuntimeWarning: invalid value encountered in scalar divide\n",
      "  ret = ret.dtype.type(ret / rcount)\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/stats/_stats_py.py:1193: RuntimeWarning: Mean of empty slice.\n",
      "  mean = a.mean(axis, keepdims=True)\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/numpy/core/_methods.py:121: RuntimeWarning: invalid value encountered in divide\n",
      "  ret = um.true_divide(\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/stats/_stats_py.py:1303: RuntimeWarning: Mean of empty slice.\n",
      "  mean = a.mean(axis, keepdims=True)\n",
      "/var/folders/l2/j581hbb53nb9hn1507fwv24w0000gn/T/ipykernel_1451/3273622910.py:31: RuntimeWarning: Precision loss occurred in moment calculation due to catastrophic cancellation. This occurs when the data are nearly identical. Results may be unreliable.\n",
      "  skew_rr = skew(np.diff(data))\n",
      "/var/folders/l2/j581hbb53nb9hn1507fwv24w0000gn/T/ipykernel_1451/3273622910.py:34: RuntimeWarning: Precision loss occurred in moment calculation due to catastrophic cancellation. This occurs when the data are nearly identical. Results may be unreliable.\n",
      "  kurt_rr = kurtosis(np.diff(data))\n",
      "/var/folders/l2/j581hbb53nb9hn1507fwv24w0000gn/T/ipykernel_1451/3273622910.py:151: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n",
      "  features[ec + \"_\" + t] = tf.map(lambda x: x[i])\n",
      "/var/folders/l2/j581hbb53nb9hn1507fwv24w0000gn/T/ipykernel_1451/3273622910.py:151: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n",
      "  features[ec + \"_\" + t] = tf.map(lambda x: x[i])\n",
      "/var/folders/l2/j581hbb53nb9hn1507fwv24w0000gn/T/ipykernel_1451/3273622910.py:151: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n",
      "  features[ec + \"_\" + t] = tf.map(lambda x: x[i])\n",
      "/var/folders/l2/j581hbb53nb9hn1507fwv24w0000gn/T/ipykernel_1451/3273622910.py:151: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n",
      "  features[ec + \"_\" + t] = tf.map(lambda x: x[i])\n",
      "/var/folders/l2/j581hbb53nb9hn1507fwv24w0000gn/T/ipykernel_1451/3273622910.py:151: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n",
      "  features[ec + \"_\" + t] = tf.map(lambda x: x[i])\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 65, using nperseg = 65\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 34, using nperseg = 34\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 29, using nperseg = 29\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 68, using nperseg = 68\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 44, using nperseg = 44\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 22, using nperseg = 22\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 39, using nperseg = 39\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 42, using nperseg = 42\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 62, using nperseg = 62\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 9, using nperseg = 9\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 25, using nperseg = 25\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 31, using nperseg = 31\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 24, using nperseg = 24\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 36, using nperseg = 36\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 27, using nperseg = 27\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 17, using nperseg = 17\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 26, using nperseg = 26\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 12, using nperseg = 12\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 32, using nperseg = 32\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 51, using nperseg = 51\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 33, using nperseg = 33\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 16, using nperseg = 16\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 38, using nperseg = 38\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 72, using nperseg = 72\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 40, using nperseg = 40\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 28, using nperseg = 28\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 82, using nperseg = 82\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 50, using nperseg = 50\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 37, using nperseg = 37\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 52, using nperseg = 52\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 56, using nperseg = 56\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 83, using nperseg = 83\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 23, using nperseg = 23\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 43, using nperseg = 43\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 30, using nperseg = 30\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 54, using nperseg = 54\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 13, using nperseg = 13\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 41, using nperseg = 41\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 35, using nperseg = 35\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 48, using nperseg = 48\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 55, using nperseg = 55\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 46, using nperseg = 46\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 69, using nperseg = 69\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 88, using nperseg = 88\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 18, using nperseg = 18\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 63, using nperseg = 63\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 10, using nperseg = 10\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 58, using nperseg = 58\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 21, using nperseg = 21\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 137, using nperseg = 137\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 60, using nperseg = 60\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 45, using nperseg = 45\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 11, using nperseg = 11\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 80, using nperseg = 80\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 64, using nperseg = 64\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 61, using nperseg = 61\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 47, using nperseg = 47\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 20, using nperseg = 20\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 102, using nperseg = 102\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 110, using nperseg = 110\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 8, using nperseg = 8\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 19, using nperseg = 19\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 57, using nperseg = 57\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 144, using nperseg = 144\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 66, using nperseg = 66\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 91, using nperseg = 91\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 84, using nperseg = 84\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 49, using nperseg = 49\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 81, using nperseg = 81\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 70, using nperseg = 70\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 15, using nperseg = 15\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 121, using nperseg = 121\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 90, using nperseg = 90\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 86, using nperseg = 86\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 71, using nperseg = 71\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 53, using nperseg = 53\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 117, using nperseg = 117\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 67, using nperseg = 67\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 73, using nperseg = 73\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 59, using nperseg = 59\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 76, using nperseg = 76\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 74, using nperseg = 74\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 100, using nperseg = 100\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 14, using nperseg = 14\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 5, using nperseg = 5\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 108, using nperseg = 108\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 78, using nperseg = 78\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 75, using nperseg = 75\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 113, using nperseg = 113\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 6, using nperseg = 6\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 114, using nperseg = 114\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 79, using nperseg = 79\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 93, using nperseg = 93\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 98, using nperseg = 98\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 135, using nperseg = 135\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 116, using nperseg = 116\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 125, using nperseg = 125\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 7, using nperseg = 7\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 130, using nperseg = 130\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 97, using nperseg = 97\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 4, using nperseg = 4\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 99, using nperseg = 99\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 2, using nperseg = 2\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 105, using nperseg = 105\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 106, using nperseg = 106\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 77, using nperseg = 77\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 101, using nperseg = 101\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 158, using nperseg = 158\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 134, using nperseg = 134\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/stats/_entropy.py:133: RuntimeWarning: invalid value encountered in divide\n",
      "  pk = 1.0*pk / np.sum(pk, axis=axis, keepdims=True)\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 126, using nperseg = 126\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 85, using nperseg = 85\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 89, using nperseg = 89\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 92, using nperseg = 92\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 104, using nperseg = 104\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 95, using nperseg = 95\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 118, using nperseg = 118\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 142, using nperseg = 142\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 1, using nperseg = 1\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 3, using nperseg = 3\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 119, using nperseg = 119\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 96, using nperseg = 96\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/var/folders/l2/j581hbb53nb9hn1507fwv24w0000gn/T/ipykernel_1451/3273622910.py:154: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n",
      "  features[ec + \"_\" + f] = ff.map(lambda x: x[i])\n",
      "/var/folders/l2/j581hbb53nb9hn1507fwv24w0000gn/T/ipykernel_1451/3273622910.py:154: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n",
      "  features[ec + \"_\" + f] = ff.map(lambda x: x[i])\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/numpy/core/_methods.py:206: RuntimeWarning: Degrees of freedom <= 0 for slice\n",
      "  ret = _var(a, axis=axis, dtype=dtype, out=out, ddof=ddof,\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/numpy/core/_methods.py:163: RuntimeWarning: invalid value encountered in divide\n",
      "  arrmean = um.true_divide(arrmean, div, out=arrmean,\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/numpy/core/_methods.py:198: RuntimeWarning: invalid value encountered in scalar divide\n",
      "  ret = ret.dtype.type(ret / rcount)\n",
      "/var/folders/l2/j581hbb53nb9hn1507fwv24w0000gn/T/ipykernel_1451/3273622910.py:157: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n",
      "  features[ec + \"_\" + p] = tf.map(lambda x: x[i])\n",
      "/var/folders/l2/j581hbb53nb9hn1507fwv24w0000gn/T/ipykernel_1451/3273622910.py:157: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n",
      "  features[ec + \"_\" + p] = tf.map(lambda x: x[i])\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/pywt/_multilevel.py:43: UserWarning: Level value of 3 is too high: all coefficients will experience boundary effects.\n",
      "  warnings.warn(\n",
      "/var/folders/l2/j581hbb53nb9hn1507fwv24w0000gn/T/ipykernel_1451/3273622910.py:162: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n",
      "  features[ec + \"_\" + w + \"_\" + str(j)] = wave.map(lambda x: x[j])\n",
      "/var/folders/l2/j581hbb53nb9hn1507fwv24w0000gn/T/ipykernel_1451/3273622910.py:162: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n",
      "  features[ec + \"_\" + w + \"_\" + str(j)] = wave.map(lambda x: x[j])\n",
      "/var/folders/l2/j581hbb53nb9hn1507fwv24w0000gn/T/ipykernel_1451/3273622910.py:162: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n",
      "  features[ec + \"_\" + w + \"_\" + str(j)] = wave.map(lambda x: x[j])\n",
      "/var/folders/l2/j581hbb53nb9hn1507fwv24w0000gn/T/ipykernel_1451/3273622910.py:162: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n",
      "  features[ec + \"_\" + w + \"_\" + str(j)] = wave.map(lambda x: x[j])\n",
      "/var/folders/l2/j581hbb53nb9hn1507fwv24w0000gn/T/ipykernel_1451/3273622910.py:162: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n",
      "  features[ec + \"_\" + w + \"_\" + str(j)] = wave.map(lambda x: x[j])\n",
      "/var/folders/l2/j581hbb53nb9hn1507fwv24w0000gn/T/ipykernel_1451/3273622910.py:162: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n",
      "  features[ec + \"_\" + w + \"_\" + str(j)] = wave.map(lambda x: x[j])\n",
      "/var/folders/l2/j581hbb53nb9hn1507fwv24w0000gn/T/ipykernel_1451/3273622910.py:162: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n",
      "  features[ec + \"_\" + w + \"_\" + str(j)] = wave.map(lambda x: x[j])\n",
      "/var/folders/l2/j581hbb53nb9hn1507fwv24w0000gn/T/ipykernel_1451/3273622910.py:162: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n",
      "  features[ec + \"_\" + w + \"_\" + str(j)] = wave.map(lambda x: x[j])\n",
      "/var/folders/l2/j581hbb53nb9hn1507fwv24w0000gn/T/ipykernel_1451/3273622910.py:168: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n",
      "  features['templates_' + m] = mf.map(lambda x: x[i])\n",
      "/var/folders/l2/j581hbb53nb9hn1507fwv24w0000gn/T/ipykernel_1451/3273622910.py:168: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n",
      "  features['templates_' + m] = mf.map(lambda x: x[i])\n",
      "/var/folders/l2/j581hbb53nb9hn1507fwv24w0000gn/T/ipykernel_1451/3273622910.py:168: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n",
      "  features['templates_' + m] = mf.map(lambda x: x[i])\n",
      "/var/folders/l2/j581hbb53nb9hn1507fwv24w0000gn/T/ipykernel_1451/3273622910.py:168: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n",
      "  features['templates_' + m] = mf.map(lambda x: x[i])\n",
      "/var/folders/l2/j581hbb53nb9hn1507fwv24w0000gn/T/ipykernel_1451/3273622910.py:168: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n",
      "  features['templates_' + m] = mf.map(lambda x: x[i])\n",
      "/var/folders/l2/j581hbb53nb9hn1507fwv24w0000gn/T/ipykernel_1451/3273622910.py:168: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n",
      "  features['templates_' + m] = mf.map(lambda x: x[i])\n",
      "/var/folders/l2/j581hbb53nb9hn1507fwv24w0000gn/T/ipykernel_1451/3273622910.py:168: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n",
      "  features['templates_' + m] = mf.map(lambda x: x[i])\n",
      "/var/folders/l2/j581hbb53nb9hn1507fwv24w0000gn/T/ipykernel_1451/3273622910.py:168: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n",
      "  features['templates_' + m] = mf.map(lambda x: x[i])\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 31, using nperseg = 31\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 17, using nperseg = 17\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 36, using nperseg = 36\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 28, using nperseg = 28\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 27, using nperseg = 27\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 72, using nperseg = 72\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 23, using nperseg = 23\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 34, using nperseg = 34\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 52, using nperseg = 52\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 49, using nperseg = 49\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 43, using nperseg = 43\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 26, using nperseg = 26\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 22, using nperseg = 22\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 41, using nperseg = 41\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 13, using nperseg = 13\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 30, using nperseg = 30\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 21, using nperseg = 21\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 35, using nperseg = 35\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 79, using nperseg = 79\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 11, using nperseg = 11\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 33, using nperseg = 33\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 32, using nperseg = 32\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 84, using nperseg = 84\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 40, using nperseg = 40\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 44, using nperseg = 44\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 29, using nperseg = 29\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 38, using nperseg = 38\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 62, using nperseg = 62\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 57, using nperseg = 57\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 39, using nperseg = 39\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 24, using nperseg = 24\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 46, using nperseg = 46\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 69, using nperseg = 69\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 25, using nperseg = 25\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 56, using nperseg = 56\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 42, using nperseg = 42\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 127, using nperseg = 127\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 16, using nperseg = 16\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 45, using nperseg = 45\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 75, using nperseg = 75\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 7, using nperseg = 7\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 20, using nperseg = 20\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 47, using nperseg = 47\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 12, using nperseg = 12\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 37, using nperseg = 37\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 51, using nperseg = 51\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 67, using nperseg = 67\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 71, using nperseg = 71\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 61, using nperseg = 61\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 85, using nperseg = 85\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 14, using nperseg = 14\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 58, using nperseg = 58\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 55, using nperseg = 55\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 64, using nperseg = 64\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 19, using nperseg = 19\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 15, using nperseg = 15\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 50, using nperseg = 50\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 90, using nperseg = 90\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 97, using nperseg = 97\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 68, using nperseg = 68\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 98, using nperseg = 98\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 59, using nperseg = 59\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 81, using nperseg = 81\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 80, using nperseg = 80\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 18, using nperseg = 18\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 60, using nperseg = 60\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 48, using nperseg = 48\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 70, using nperseg = 70\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 8, using nperseg = 8\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 63, using nperseg = 63\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 76, using nperseg = 76\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 78, using nperseg = 78\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 54, using nperseg = 54\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 65, using nperseg = 65\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 107, using nperseg = 107\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 9, using nperseg = 9\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 122, using nperseg = 122\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 102, using nperseg = 102\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 89, using nperseg = 89\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 53, using nperseg = 53\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 66, using nperseg = 66\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 94, using nperseg = 94\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 162, using nperseg = 162\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 74, using nperseg = 74\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 73, using nperseg = 73\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 88, using nperseg = 88\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 111, using nperseg = 111\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 77, using nperseg = 77\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 101, using nperseg = 101\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 117, using nperseg = 117\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 112, using nperseg = 112\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 110, using nperseg = 110\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 10, using nperseg = 10\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 100, using nperseg = 100\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 93, using nperseg = 93\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 118, using nperseg = 118\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 83, using nperseg = 83\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 86, using nperseg = 86\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 95, using nperseg = 95\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 103, using nperseg = 103\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 134, using nperseg = 134\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 137, using nperseg = 137\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 106, using nperseg = 106\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 87, using nperseg = 87\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 92, using nperseg = 92\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 91, using nperseg = 91\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 173, using nperseg = 173\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 125, using nperseg = 125\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 96, using nperseg = 96\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 200, using nperseg = 200\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 108, using nperseg = 108\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 82, using nperseg = 82\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 119, using nperseg = 119\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/pywt/_multilevel.py:43: UserWarning: Level value of 3 is too high: all coefficients will experience boundary effects.\n",
      "  warnings.warn(\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 180, using nperseg = 180\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 180, using nperseg = 180\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/numpy/core/fromnumeric.py:3504: RuntimeWarning: Mean of empty slice.\n",
      "  return _methods._mean(a, axis=axis, dtype=dtype,\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide\n",
      "  ret = ret.dtype.type(ret / rcount)\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/numpy/core/_methods.py:206: RuntimeWarning: Degrees of freedom <= 0 for slice\n",
      "  ret = _var(a, axis=axis, dtype=dtype, out=out, ddof=ddof,\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/numpy/core/_methods.py:163: RuntimeWarning: invalid value encountered in divide\n",
      "  arrmean = um.true_divide(arrmean, div, out=arrmean,\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/numpy/core/_methods.py:198: RuntimeWarning: invalid value encountered in scalar divide\n",
      "  ret = ret.dtype.type(ret / rcount)\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/stats/_stats_py.py:1193: RuntimeWarning: Mean of empty slice.\n",
      "  mean = a.mean(axis, keepdims=True)\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/numpy/core/_methods.py:121: RuntimeWarning: invalid value encountered in divide\n",
      "  ret = um.true_divide(\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/stats/_stats_py.py:1303: RuntimeWarning: Mean of empty slice.\n",
      "  mean = a.mean(axis, keepdims=True)\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 30, using nperseg = 30\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 16, using nperseg = 16\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 29, using nperseg = 29\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 27, using nperseg = 27\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 26, using nperseg = 26\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 17, using nperseg = 17\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 70, using nperseg = 70\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 22, using nperseg = 22\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 33, using nperseg = 33\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 51, using nperseg = 51\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 45, using nperseg = 45\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 42, using nperseg = 42\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 25, using nperseg = 25\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 21, using nperseg = 21\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 40, using nperseg = 40\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 12, using nperseg = 12\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 20, using nperseg = 20\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 34, using nperseg = 34\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 78, using nperseg = 78\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 10, using nperseg = 10\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 32, using nperseg = 32\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 28, using nperseg = 28\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 83, using nperseg = 83\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 35, using nperseg = 35\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 31, using nperseg = 31\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 48, using nperseg = 48\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 37, using nperseg = 37\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 43, using nperseg = 43\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 49, using nperseg = 49\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 56, using nperseg = 56\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 39, using nperseg = 39\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 68, using nperseg = 68\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 24, using nperseg = 24\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 55, using nperseg = 55\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 41, using nperseg = 41\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 126, using nperseg = 126\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 50, using nperseg = 50\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 15, using nperseg = 15\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 74, using nperseg = 74\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 6, using nperseg = 6\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 18, using nperseg = 18\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 46, using nperseg = 46\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 11, using nperseg = 11\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 36, using nperseg = 36\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 23, using nperseg = 23\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 63, using nperseg = 63\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 69, using nperseg = 69\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 60, using nperseg = 60\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 13, using nperseg = 13\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 19, using nperseg = 19\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 38, using nperseg = 38\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 44, using nperseg = 44\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 54, using nperseg = 54\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 14, using nperseg = 14\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 57, using nperseg = 57\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 96, using nperseg = 96\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 95, using nperseg = 95\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 80, using nperseg = 80\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 67, using nperseg = 67\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 79, using nperseg = 79\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 62, using nperseg = 62\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 58, using nperseg = 58\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 8, using nperseg = 8\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 61, using nperseg = 61\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 47, using nperseg = 47\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 59, using nperseg = 59\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 65, using nperseg = 65\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 7, using nperseg = 7\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 66, using nperseg = 66\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 75, using nperseg = 75\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 77, using nperseg = 77\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 53, using nperseg = 53\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 73, using nperseg = 73\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 64, using nperseg = 64\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 106, using nperseg = 106\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 4, using nperseg = 4\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 117, using nperseg = 117\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 101, using nperseg = 101\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 5, using nperseg = 5\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 88, using nperseg = 88\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 52, using nperseg = 52\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 93, using nperseg = 93\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 161, using nperseg = 161\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 81, using nperseg = 81\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 2, using nperseg = 2\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 109, using nperseg = 109\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 100, using nperseg = 100\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 89, using nperseg = 89\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 115, using nperseg = 115\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 9, using nperseg = 9\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 111, using nperseg = 111\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 71, using nperseg = 71\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 110, using nperseg = 110\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 98, using nperseg = 98\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 92, using nperseg = 92\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 84, using nperseg = 84\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 91, using nperseg = 91\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 82, using nperseg = 82\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 85, using nperseg = 85\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 94, using nperseg = 94\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 87, using nperseg = 87\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 102, using nperseg = 102\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 86, using nperseg = 86\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 133, using nperseg = 133\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 128, using nperseg = 128\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 105, using nperseg = 105\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 76, using nperseg = 76\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 97, using nperseg = 97\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 124, using nperseg = 124\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 3, using nperseg = 3\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 172, using nperseg = 172\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 72, using nperseg = 72\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 107, using nperseg = 107\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 118, using nperseg = 118\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 99, using nperseg = 99\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/numpy/core/_methods.py:206: RuntimeWarning: Degrees of freedom <= 0 for slice\n",
      "  ret = _var(a, axis=axis, dtype=dtype, out=out, ddof=ddof,\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/numpy/core/_methods.py:198: RuntimeWarning: invalid value encountered in scalar divide\n",
      "  ret = ret.dtype.type(ret / rcount)\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/numpy/core/_methods.py:163: RuntimeWarning: invalid value encountered in divide\n",
      "  arrmean = um.true_divide(arrmean, div, out=arrmean,\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/pywt/_multilevel.py:43: UserWarning: Level value of 3 is too high: all coefficients will experience boundary effects.\n",
      "  warnings.warn(\n",
      "/var/folders/l2/j581hbb53nb9hn1507fwv24w0000gn/T/ipykernel_1451/3273622910.py:162: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n",
      "  features[ec + \"_\" + w + \"_\" + str(j)] = wave.map(lambda x: x[j])\n",
      "/var/folders/l2/j581hbb53nb9hn1507fwv24w0000gn/T/ipykernel_1451/3273622910.py:162: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n",
      "  features[ec + \"_\" + w + \"_\" + str(j)] = wave.map(lambda x: x[j])\n",
      "/var/folders/l2/j581hbb53nb9hn1507fwv24w0000gn/T/ipykernel_1451/3273622910.py:162: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n",
      "  features[ec + \"_\" + w + \"_\" + str(j)] = wave.map(lambda x: x[j])\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/numpy/core/fromnumeric.py:3504: RuntimeWarning: Mean of empty slice.\n",
      "  return _methods._mean(a, axis=axis, dtype=dtype,\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/numpy/core/_methods.py:129: RuntimeWarning: invalid value encountered in scalar divide\n",
      "  ret = ret.dtype.type(ret / rcount)\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/numpy/core/_methods.py:206: RuntimeWarning: Degrees of freedom <= 0 for slice\n",
      "  ret = _var(a, axis=axis, dtype=dtype, out=out, ddof=ddof,\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/numpy/core/_methods.py:163: RuntimeWarning: invalid value encountered in divide\n",
      "  arrmean = um.true_divide(arrmean, div, out=arrmean,\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/numpy/core/_methods.py:198: RuntimeWarning: invalid value encountered in scalar divide\n",
      "  ret = ret.dtype.type(ret / rcount)\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/stats/_stats_py.py:1193: RuntimeWarning: Mean of empty slice.\n",
      "  mean = a.mean(axis, keepdims=True)\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/numpy/core/_methods.py:121: RuntimeWarning: invalid value encountered in divide\n",
      "  ret = um.true_divide(\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/stats/_stats_py.py:1303: RuntimeWarning: Mean of empty slice.\n",
      "  mean = a.mean(axis, keepdims=True)\n",
      "/var/folders/l2/j581hbb53nb9hn1507fwv24w0000gn/T/ipykernel_1451/3273622910.py:31: RuntimeWarning: Precision loss occurred in moment calculation due to catastrophic cancellation. This occurs when the data are nearly identical. Results may be unreliable.\n",
      "  skew_rr = skew(np.diff(data))\n",
      "/var/folders/l2/j581hbb53nb9hn1507fwv24w0000gn/T/ipykernel_1451/3273622910.py:34: RuntimeWarning: Precision loss occurred in moment calculation due to catastrophic cancellation. This occurs when the data are nearly identical. Results may be unreliable.\n",
      "  kurt_rr = kurtosis(np.diff(data))\n",
      "/var/folders/l2/j581hbb53nb9hn1507fwv24w0000gn/T/ipykernel_1451/3273622910.py:151: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n",
      "  features[ec + \"_\" + t] = tf.map(lambda x: x[i])\n",
      "/var/folders/l2/j581hbb53nb9hn1507fwv24w0000gn/T/ipykernel_1451/3273622910.py:151: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n",
      "  features[ec + \"_\" + t] = tf.map(lambda x: x[i])\n",
      "/var/folders/l2/j581hbb53nb9hn1507fwv24w0000gn/T/ipykernel_1451/3273622910.py:151: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n",
      "  features[ec + \"_\" + t] = tf.map(lambda x: x[i])\n",
      "/var/folders/l2/j581hbb53nb9hn1507fwv24w0000gn/T/ipykernel_1451/3273622910.py:151: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n",
      "  features[ec + \"_\" + t] = tf.map(lambda x: x[i])\n",
      "/var/folders/l2/j581hbb53nb9hn1507fwv24w0000gn/T/ipykernel_1451/3273622910.py:151: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n",
      "  features[ec + \"_\" + t] = tf.map(lambda x: x[i])\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 30, using nperseg = 30\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 16, using nperseg = 16\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 29, using nperseg = 29\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 27, using nperseg = 27\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 26, using nperseg = 26\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 17, using nperseg = 17\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 70, using nperseg = 70\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 22, using nperseg = 22\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 33, using nperseg = 33\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 51, using nperseg = 51\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 45, using nperseg = 45\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 42, using nperseg = 42\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 25, using nperseg = 25\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 21, using nperseg = 21\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 40, using nperseg = 40\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 12, using nperseg = 12\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 20, using nperseg = 20\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 34, using nperseg = 34\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 78, using nperseg = 78\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 10, using nperseg = 10\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 32, using nperseg = 32\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 28, using nperseg = 28\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 83, using nperseg = 83\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 35, using nperseg = 35\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 31, using nperseg = 31\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 48, using nperseg = 48\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 37, using nperseg = 37\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 43, using nperseg = 43\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 49, using nperseg = 49\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 56, using nperseg = 56\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 39, using nperseg = 39\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 68, using nperseg = 68\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 24, using nperseg = 24\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 55, using nperseg = 55\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 41, using nperseg = 41\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 126, using nperseg = 126\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 50, using nperseg = 50\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 15, using nperseg = 15\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 74, using nperseg = 74\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 6, using nperseg = 6\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 18, using nperseg = 18\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 46, using nperseg = 46\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 11, using nperseg = 11\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 36, using nperseg = 36\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 23, using nperseg = 23\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 63, using nperseg = 63\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 69, using nperseg = 69\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 60, using nperseg = 60\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 13, using nperseg = 13\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 19, using nperseg = 19\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 38, using nperseg = 38\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 44, using nperseg = 44\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 54, using nperseg = 54\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 14, using nperseg = 14\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 57, using nperseg = 57\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 96, using nperseg = 96\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 95, using nperseg = 95\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 80, using nperseg = 80\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 67, using nperseg = 67\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 79, using nperseg = 79\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 62, using nperseg = 62\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 58, using nperseg = 58\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 8, using nperseg = 8\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 61, using nperseg = 61\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 47, using nperseg = 47\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 59, using nperseg = 59\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 65, using nperseg = 65\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 7, using nperseg = 7\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 66, using nperseg = 66\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 75, using nperseg = 75\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 77, using nperseg = 77\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 53, using nperseg = 53\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 73, using nperseg = 73\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 64, using nperseg = 64\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 106, using nperseg = 106\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 4, using nperseg = 4\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 117, using nperseg = 117\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 101, using nperseg = 101\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 5, using nperseg = 5\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 88, using nperseg = 88\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 52, using nperseg = 52\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 93, using nperseg = 93\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 161, using nperseg = 161\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 81, using nperseg = 81\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 2, using nperseg = 2\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 109, using nperseg = 109\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 100, using nperseg = 100\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 89, using nperseg = 89\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 115, using nperseg = 115\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 9, using nperseg = 9\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 111, using nperseg = 111\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 71, using nperseg = 71\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 110, using nperseg = 110\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 98, using nperseg = 98\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 92, using nperseg = 92\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 84, using nperseg = 84\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 91, using nperseg = 91\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 82, using nperseg = 82\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 85, using nperseg = 85\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 94, using nperseg = 94\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 87, using nperseg = 87\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 102, using nperseg = 102\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 86, using nperseg = 86\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 133, using nperseg = 133\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 128, using nperseg = 128\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 105, using nperseg = 105\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 76, using nperseg = 76\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 97, using nperseg = 97\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 124, using nperseg = 124\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 3, using nperseg = 3\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 172, using nperseg = 172\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 72, using nperseg = 72\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 107, using nperseg = 107\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 118, using nperseg = 118\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/scipy/signal/_spectral_py.py:2017: UserWarning: nperseg = 256 is greater than input length  = 99, using nperseg = 99\n",
      "  warnings.warn('nperseg = {0:d} is greater than input length '\n",
      "/var/folders/l2/j581hbb53nb9hn1507fwv24w0000gn/T/ipykernel_1451/3273622910.py:154: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n",
      "  features[ec + \"_\" + f] = ff.map(lambda x: x[i])\n",
      "/var/folders/l2/j581hbb53nb9hn1507fwv24w0000gn/T/ipykernel_1451/3273622910.py:154: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n",
      "  features[ec + \"_\" + f] = ff.map(lambda x: x[i])\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/numpy/core/_methods.py:206: RuntimeWarning: Degrees of freedom <= 0 for slice\n",
      "  ret = _var(a, axis=axis, dtype=dtype, out=out, ddof=ddof,\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/numpy/core/_methods.py:198: RuntimeWarning: invalid value encountered in scalar divide\n",
      "  ret = ret.dtype.type(ret / rcount)\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/numpy/core/_methods.py:163: RuntimeWarning: invalid value encountered in divide\n",
      "  arrmean = um.true_divide(arrmean, div, out=arrmean,\n",
      "/var/folders/l2/j581hbb53nb9hn1507fwv24w0000gn/T/ipykernel_1451/3273622910.py:157: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n",
      "  features[ec + \"_\" + p] = tf.map(lambda x: x[i])\n",
      "/var/folders/l2/j581hbb53nb9hn1507fwv24w0000gn/T/ipykernel_1451/3273622910.py:157: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n",
      "  features[ec + \"_\" + p] = tf.map(lambda x: x[i])\n",
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/pywt/_multilevel.py:43: UserWarning: Level value of 3 is too high: all coefficients will experience boundary effects.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(5117, 127) (3411, 127)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/l2/j581hbb53nb9hn1507fwv24w0000gn/T/ipykernel_1451/3273622910.py:162: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n",
      "  features[ec + \"_\" + w + \"_\" + str(j)] = wave.map(lambda x: x[j])\n",
      "/var/folders/l2/j581hbb53nb9hn1507fwv24w0000gn/T/ipykernel_1451/3273622910.py:162: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n",
      "  features[ec + \"_\" + w + \"_\" + str(j)] = wave.map(lambda x: x[j])\n",
      "/var/folders/l2/j581hbb53nb9hn1507fwv24w0000gn/T/ipykernel_1451/3273622910.py:162: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n",
      "  features[ec + \"_\" + w + \"_\" + str(j)] = wave.map(lambda x: x[j])\n",
      "/var/folders/l2/j581hbb53nb9hn1507fwv24w0000gn/T/ipykernel_1451/3273622910.py:162: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n",
      "  features[ec + \"_\" + w + \"_\" + str(j)] = wave.map(lambda x: x[j])\n",
      "/var/folders/l2/j581hbb53nb9hn1507fwv24w0000gn/T/ipykernel_1451/3273622910.py:162: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n",
      "  features[ec + \"_\" + w + \"_\" + str(j)] = wave.map(lambda x: x[j])\n",
      "/var/folders/l2/j581hbb53nb9hn1507fwv24w0000gn/T/ipykernel_1451/3273622910.py:162: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n",
      "  features[ec + \"_\" + w + \"_\" + str(j)] = wave.map(lambda x: x[j])\n",
      "/var/folders/l2/j581hbb53nb9hn1507fwv24w0000gn/T/ipykernel_1451/3273622910.py:162: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n",
      "  features[ec + \"_\" + w + \"_\" + str(j)] = wave.map(lambda x: x[j])\n",
      "/var/folders/l2/j581hbb53nb9hn1507fwv24w0000gn/T/ipykernel_1451/3273622910.py:162: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n",
      "  features[ec + \"_\" + w + \"_\" + str(j)] = wave.map(lambda x: x[j])\n",
      "/var/folders/l2/j581hbb53nb9hn1507fwv24w0000gn/T/ipykernel_1451/3273622910.py:168: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n",
      "  features['templates_' + m] = mf.map(lambda x: x[i])\n",
      "/var/folders/l2/j581hbb53nb9hn1507fwv24w0000gn/T/ipykernel_1451/3273622910.py:168: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n",
      "  features['templates_' + m] = mf.map(lambda x: x[i])\n",
      "/var/folders/l2/j581hbb53nb9hn1507fwv24w0000gn/T/ipykernel_1451/3273622910.py:168: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n",
      "  features['templates_' + m] = mf.map(lambda x: x[i])\n",
      "/var/folders/l2/j581hbb53nb9hn1507fwv24w0000gn/T/ipykernel_1451/3273622910.py:168: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n",
      "  features['templates_' + m] = mf.map(lambda x: x[i])\n",
      "/var/folders/l2/j581hbb53nb9hn1507fwv24w0000gn/T/ipykernel_1451/3273622910.py:168: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n",
      "  features['templates_' + m] = mf.map(lambda x: x[i])\n",
      "/var/folders/l2/j581hbb53nb9hn1507fwv24w0000gn/T/ipykernel_1451/3273622910.py:168: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n",
      "  features['templates_' + m] = mf.map(lambda x: x[i])\n",
      "/var/folders/l2/j581hbb53nb9hn1507fwv24w0000gn/T/ipykernel_1451/3273622910.py:168: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n",
      "  features['templates_' + m] = mf.map(lambda x: x[i])\n",
      "/var/folders/l2/j581hbb53nb9hn1507fwv24w0000gn/T/ipykernel_1451/3273622910.py:168: PerformanceWarning: DataFrame is highly fragmented.  This is usually the result of calling `frame.insert` many times, which has poor performance.  Consider joining all columns at once using pd.concat(axis=1) instead. To get a de-fragmented frame, use `newframe = frame.copy()`\n",
      "  features['templates_' + m] = mf.map(lambda x: x[i])\n"
     ]
    }
   ],
   "source": [
    "train_features = extract_features(X, X.shape[0])\n",
    "out_features = extract_features(X_out, X_out.shape[0])\n",
    "\n",
    "print(train_features.shape, out_features.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.svm import SVC\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.metrics import f1_score\n",
    "from sklearn.impute import SimpleImputer\n",
    "\n",
    "\n",
    "def train_model(X_data, y_data, model):\n",
    "    X_model = X_data.to_numpy()\n",
    "    y_model = y_data.to_numpy().ravel()\n",
    "\n",
    "    imputer = SimpleImputer(strategy='median')\n",
    "    X_model = imputer.fit_transform(X_model)\n",
    "\n",
    "    X_train, X_test, y_train, y_test = train_test_split(X_model, y_model, test_size=0.2, random_state=42)\n",
    "    \n",
    "    model.fit(X_train, y_train)\n",
    "\n",
    "    y_pred = model.predict(X_test)\n",
    "\n",
    "    f1 = f1_score(y_test, y_pred, average='micro')\n",
    "\n",
    "    print(\"F1 Score:\", f1)\n",
    "    return f1\n",
    "\n",
    "def predict_model(X_data, model):\n",
    "    X_model = X_data.to_numpy()\n",
    "\n",
    "    imputer = SimpleImputer(strategy='median')\n",
    "    X_model = imputer.fit_transform(X_model)\n",
    "\n",
    "    y_pred = model.predict(X_model)\n",
    "\n",
    "    return y_pred\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training Logistic Regression...\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/mchami/anaconda3/envs/amltask2/lib/python3.9/site-packages/sklearn/linear_model/_logistic.py:460: ConvergenceWarning: lbfgs failed to converge (status=1):\n",
      "STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.\n",
      "\n",
      "Increase the number of iterations (max_iter) or scale the data as shown in:\n",
      "    https://scikit-learn.org/stable/modules/preprocessing.html\n",
      "Please also refer to the documentation for alternative solver options:\n",
      "    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression\n",
      "  n_iter_i = _check_optimize_result(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "F1 Score: 0.482421875\n",
      "Logistic Regression F1 Score: 0.482421875\n",
      "\n",
      "Training SVM...\n",
      "F1 Score: 0.44921875\n",
      "SVM F1 Score: 0.44921875\n",
      "\n",
      "Training Decision Tree...\n",
      "F1 Score: 0.4814453125\n",
      "Decision Tree F1 Score: 0.4814453125\n",
      "\n",
      "Training Random Forest...\n",
      "F1 Score: 0.580078125\n",
      "Random Forest F1 Score: 0.580078125\n",
      "\n",
      "Training K-Nearest Neighbors...\n",
      "F1 Score: 0.5654296875\n",
      "K-Nearest Neighbors F1 Score: 0.5654296875\n",
      "\n",
      "Training Naive Bayes...\n",
      "F1 Score: 0.08203125\n",
      "Naive Bayes F1 Score: 0.08203125\n",
      "\n",
      "Training Neural Network...\n",
      "F1 Score: 0.5751953125\n",
      "Neural Network F1 Score: 0.5751953125\n",
      "\n",
      "Training Gradient Boosting...\n",
      "F1 Score: 0.5703125\n",
      "Gradient Boosting F1 Score: 0.5703125\n",
      "\n"
     ]
    }
   ],
   "source": [
    "from sklearn.linear_model import LogisticRegression\n",
    "from sklearn.ensemble import RandomForestClassifier\n",
    "from sklearn.tree import DecisionTreeClassifier\n",
    "from sklearn.neighbors import KNeighborsClassifier\n",
    "from sklearn.naive_bayes import GaussianNB\n",
    "from sklearn.neural_network import MLPClassifier\n",
    "from sklearn.ensemble import GradientBoostingClassifier\n",
    "\n",
    "# Define the models\n",
    "models = [\n",
    "    ('Logistic Regression', LogisticRegression(multi_class='multinomial', random_state=42)),\n",
    "    ('SVM', SVC(kernel='linear', C=1.0, random_state=42)),\n",
    "    ('Decision Tree', DecisionTreeClassifier(random_state=42)),\n",
    "    ('Random Forest', RandomForestClassifier(random_state=42)),\n",
    "    ('K-Nearest Neighbors', KNeighborsClassifier()),\n",
    "    ('Naive Bayes', GaussianNB()),\n",
    "    ('Neural Network', MLPClassifier(random_state=42)),\n",
    "    ('Gradient Boosting', GradientBoostingClassifier(random_state=42))\n",
    "]\n",
    "\n",
    "# Train and evaluate each model\n",
    "for name, model in models:\n",
    "    print(f\"Training {name}...\")\n",
    "    f1 = train_model(X, y, model)\n",
    "    print(f\"{name} F1 Score: {f1}\\n\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "F1 Score: 0.44921875\n",
      "0.44921875\n"
     ]
    }
   ],
   "source": [
    "svm = SVC(kernel='linear', C=1.0, random_state=42)\n",
    "f1 = train_model(X, y, svm)\n",
    "print(f1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "out = pd.DataFrame(index=X_out.index, columns=['y'])\n",
    "y_out = predict_model(out_features, svm)\n",
    "out['y'] = y_out\n",
    "out.to_csv(\"out.csv\")"
   ]
  }
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